4 papers
JASPR: Joint Spatial Representation learning of histology and spatial genomics for improved virtual genomic screening and clinical prognostication
Marija Pizurica, Eric Zimmermann, Neil Tenenholtz +5
Recent studies have shown that spatial properties of tumors are critical for understanding disease biology and predicting patient outcomes. These spatial properties are increasingl…
Integrating chemical structures as treatments improves representations of microscopy images for morphological profiling
Yemin Yu, Emre Hayir, Neil Tenenholtz +5
Recent advances in self-supervised deep learning have improved our ability to quantify cellular morphological changes in high-throughput microscopy screens, a process known as morp…
Multimodal Alignment Improves Generalizability of Genomic Biomarker Prediction in Computational Pathology
Ekaterina Redekop, Eric Zimmermann, Ava P Amini +5
Computational pathology models that use digitized histopathology whole-slide images have the potential to become a cost-effective and scalable alternative to molecular assays for t…
Towards deep learning sequence-structure co-generation for protein design
Chentong Wang, Sarah Alamdari, Carles Domingo-Enrich +2
Deep generative models that learn from the distribution of natural protein sequences and structures may enable the design of new proteins with valuable functions. While the majorit…